Your search found 5 records
1 Verdin, J. P.; Crane, M. P.; Lyford, G. P. 1985. Application of a digital geographic data base to irrigation water rights management. In Johnson, A. I.; Rango, A. Remote sensing applications for consumptive use (Evapotranspiration): Papers presented at 21st annual AWRA conference and symposium, Tucson, Arizona, 11-16 August 1985. Bethesda, MA, USA: AWRA. pp.35-50.
(Location: IWMI-HQ Call no: 621.3678 G000 JOH Record No: H09411)
2 Eckhardt, D. W.; Verdin, J. P.. 1990. Automated update of an irrigated lands GIS using SPOT HRV imagery. Photogrammetric Engineering and Remote Sensing, 56(11):1515-1522.
(Location: IWMI-HQ Call no: P 2124 Record No: H010528)
3 Senay, G. B.; Budde, M. E.; Verdin, J. P.; Rowland, J. 2009. Estimating actual evapotranspiration from irrigated fields using a simplified surface energy balance approach. In Thenkabail, P. S.; Lyon, J. G.; Turral, H.; Biradar, C. M. (Eds.). Remote sensing of global croplands for food security. Boca Raton, FL, USA: CRC Press. pp.317-329. (Taylor & Francis Series in Remote Sensing Applications)
Remote sensing ; Evapotranspiration ; Estimation ; Irrigated land ; Energy balance / Afghanistan / Baghlan province
(Location: IWMI HQ Call no: 631.7.1 G000 THE Record No: H042428)
4 Wardlow, B. D.; Anderson, M. C.; Verdin, J. P.. (Eds.) 2012. Remote sensing of drought: innovative monitoring approaches. Boca Raton, FL, USA: CRC Press. 422p.
Remote sensing ; Drought ; Monitoring ; History ; Vegetation ; Precipitation ; Indicators ; Evapotranspiration ; Water balance ; Energy balance ; Satellite surveys ; Satellite imagery ; Data analysis ; Analytical methods ; Soil moisture ; Rain ; Temperature ; Snow cover ; Early warning systems ; Models / Kenya / Eastern Africa / Sahel
(Location: IWMI HQ Call no: 621.3678 G000 WAR Record No: H045035)
(0.46 MB)
5 Arsenault, K. R.; Shukla, S.; Hazra, A.; Getirana, A.; McNally, A.; Kumar, S. V.; Koster, R. D.; Peters-Lidard, C. D.; Zaitchik, B. F.; Badr, H.; Jung, H. C.; Narapusetty, B.; Navari, M.; Wang, S.; Mocko, D. M.; Funk, C.; Harrison, L.; Husak, G. J.; Adoum, A.; Galu, G.; Magadzire, T.; Roningen, J.; Shaw, M.; Eylander, J.; Bergaoui, K.; McDonnell, Rachael A.; Verdin, J. P.. 2020. The NASA hydrological forecast system for food and water security applications. Bulletin of the American Meteorological Society (BAMS), 101(7):E1007-E1025. [doi: https://doi.org/10.1175/BAMS-D-18-0264.1]
Hydrology ; Forecasting ; Early warning systems ; Food security ; Water security ; Drought ; Flooding ; Precipitation ; Groundwater ; Water storage ; Soil water content ; Stream flow ; Monitoring ; Land area ; Meteorological factors ; Satellite observation ; Modelling / Africa / Middle East
(Location: IWMI HQ Call no: e-copy only Record No: H049803)
https://journals.ametsoc.org/bams/article-pdf/101/7/E1007/4981535/bamsd180264.pdf
https://vlibrary.iwmi.org/pdf/H049803.pdf
https://vlibrary.iwmi.org/pdf/H049803.pdf
(8.47 MB) (8.47 MB)
Many regions in Africa and the Middle East are vulnerable to drought and to water and food insecurity, motivating agency efforts such as the U.S. Agency for International Development’s (USAID) Famine Early Warning Systems Network (FEWS NET) to provide early warning of drought events in the region. Each year these warnings guide life-saving assistance that reaches millions of people. A new NASA multimodel, remote sensing–based hydrological forecasting and analysis system, NHyFAS, has been developed to support such efforts by improving the FEWS NET’s current early warning capabilities. NHyFAS derives its skill from two sources: (i) accurate initial conditions, as produced by an offline land modeling system through the application and/or assimilation of various satellite data (precipitation, soil moisture, and terrestrial water storage), and (ii) meteorological forcing data during the forecast period as produced by a state-of-the-art ocean–land–atmosphere forecast system. The land modeling framework used is the Land Information System (LIS), which employs a suite of land surface models, allowing multimodel ensembles and multiple data assimilation strategies to better estimate land surface conditions. An evaluation of NHyFAS shows that its 1–5-month hindcasts successfully capture known historic drought events, and it has improved skill over benchmark-type hindcasts. The system also benefits from strong collaboration with end-user partners in Africa and the Middle East, who provide insights on strategies to formulate and communicate early warning indicators to water and food security communities. The additional lead time provided by this system will increase the speed, accuracy, and efficacy of humanitarian disaster relief, helping to save lives and livelihoods.
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